Most AI agents can call tools. The harder part is knowing how those tools should actually be used.
With SciAgentKit, computational drug-discovery workflows are guided by skills written by domain experts. These skills encode tool selection, parameter choices, validation checks, and scientific decision rules across ligand preparation, PDB selection, pocket detection, docking, molecular dynamics, and trajectory analysis.
The calculations are performed by established scientific software, while the agent follows expert-defined workflow logic.
The aim is to make advanced drug-discovery workflows more reproducible, consistent, and easier to run through natural language.
MCP-native scientific tools for reproducible computational biology and AI-driven drug discovery. No hallucinated descriptors, docking scores, or RMSD.
Connect Claude code, Cursor, Gemini cli and Codex to real local tools for molecular analysis, docking, molecular dynamics and reproducible scientific reporting.
